Answer:
We use it in everyday life to do things such as Money or Population. Like your pay could go up or the population somewhere can increase to a point where the country or town has to raise prices or lower them, and get more of something.
Example:
You have someone babysit for you and you give them $15 a hour. They do a lot less work then you expected and spent most of the time looking at there phone. You might lower the pay due to them most the time just playing on there phone.
The answer is sweaty pig feet hope this helps
Answer:
send the expression please
Answer:
1.225 × 10 to the power 5 + 3.655 × 10³ = 1.26155 x 10 to the power 5
Step-by-step explanation:
Standard Notation:
122500 + 3655 = 1.26155 x 10 to the power 5
Scientific Notation:
1.225 × 10 to the power 5 + 3.655 × 10³ = 1.26155 x 10 to the power 5
E Notation:
1.225e5 + 3.655e3 = 1.26155e5
Answer:
A. 110 pounds,
C. 281 pounds
Step-by-step explanation:
Problems of normally distributed samples can be solved using the z-score formula.
In a set with mean
and standard deviation
, the zscore of a measure X is given by:
![Z = \frac{X - \mu}{\sigma}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7B%5Csigma%7D)
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
A measure is said to be an outlier if it has a pvalue lesser than 0.05 or higher than 0.95.
In this problem, we have that:
![\mu = 173, \sigma = 30](https://tex.z-dn.net/?f=%5Cmu%20%3D%20173%2C%20%5Csigma%20%3D%2030)
A. 110 pounds,
![Z = \frac{X - \mu}{\sigma}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7B%5Csigma%7D)
![Z = \frac{110 - 173}{30}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7B110%20-%20173%7D%7B30%7D)
![Z = -2.1](https://tex.z-dn.net/?f=Z%20%3D%20-2.1)
has a pvalue of 0.0179. So a weight of 110 pounds is an outlier.
B. 157 pounds,
![Z = \frac{X - \mu}{\sigma}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7B%5Csigma%7D)
![Z = \frac{157 - 173}{30}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7B157%20-%20173%7D%7B30%7D)
![Z = 0.53](https://tex.z-dn.net/?f=Z%20%3D%200.53)
has a pvalue of 0.702.
So a weight of 157 is not an outlier.
C. 281 pounds
![Z = \frac{X - \mu}{\sigma}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7B%5Csigma%7D)
![Z = \frac{281 - 173}{30}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7B281%20-%20173%7D%7B30%7D)
![Z = 3.6](https://tex.z-dn.net/?f=Z%20%3D%203.6)
has a pvalue of 0.9988.
So a weight of 281 is an outlier.